Parallel Computing

A seminar about Parallel Computing

A CPU is a microprocessor -- a computing engine on a chip. Whilemodern microprocessors are small, they're also really powerful. They caninterpret millions of instructions per second. Even so, there are somecomputational problems that are so complex that a powerful microprocessorwould require years to solve them.Computer scientists use different approaches to address this problem. Onepotential approach is to push for more powerful microprocessors. Usually thismeans finding ways to fit more transistors on a microprocessor chip.Computer engineers are already building microprocessors with transistors thatare only a few dozen nanometers wide. How small is a nanometer? It's onebillionthof a meter. A red blood cell has a diameter of 2,500 nanometers -- thewidth of modern transistors is a fraction of that size.Building more powerful microprocessors requires an intense and expensiveproduction process. Some computational problems take years to solve evenwith the benefit of a more powerful microprocessor. Partly because of thesefactors, computer scientists sometimes use a different approach: parallelprocessing.In general, parallel processing means that at least two microprocessors handleparts of an overall task. The concept is pretty simple: A computer scientistdivides a complex problem into component parts using special softwarespecifically designed for the task. He or she then assigns each component partto a dedicated processor. Each processor solves its part of the overallcomputational problem. The software reassembles the data to reach the endconclusion of the original complex problem.